In recent years, there has been a growing sentiment (supported by anecdotal evidence) that the long-term effects of advertising is diminishing. Hypothesized causes include:
- Growing impact of digital and information availability in consumer shopping and search processes.
- Decreasing (product) brand loyalty.
- Consumer culture of “here and now” and fleeting consumer interests across product and shopping categories.
- Growing plethora of consumer choices in almost any product category.
A recent study conducted by Nielsen Catalina, Kellogg, and CBS concludes that the long-term effect – defined as total sales lift – range from 1.8 to 4.5 times the short-term sales lift. Such estimates of long-term effects are even higher than similar assessments almost three decades back, further questioning anecdotal evidence. The wide variation in long-term effects across brands and categories, further highlights the importance of precisely estimating and incorporating the effects in marketing investment optimization.
In order to tease out the long-term effects of advertising investments, we need more granular data on marketing investments within each media and marketing channel, and sales.
- Higher temporal resolution: Hourly and daily marketing stimuli and investment data instead of typical weekly and monthly data.
- Improved spatial resolution: Investments tracked across markets – DMAs, states, etc.
- More precise targeting resolution: Who is exposed to the advertising? visitors versus prospects versus customers?
- Disaggregate customer and sales data: Sales from existing customers versus new customers? Conversions rates – prospect to new customer to repeat customer? Frequency of purchases by customer type? Order value by customer type? Customer-level sales data?
- Test and control: Often, there is the need to design and execute structured experiments to generate the granular data for estimating long-term effects.
- Go beyond sales and profit: To evaluate lasting effects of advertising, we need to marry brand tracking data with marketing effectiveness analysis.
Collating data spanning the upper and lower paths of the customer decision journey and statistically analyzing the interrelationships provides a stronger foundation for marketing investment decisions.